Instructions to use tiny-random/deepseek-v3.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tiny-random/deepseek-v3.1 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="tiny-random/deepseek-v3.1", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("tiny-random/deepseek-v3.1", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("tiny-random/deepseek-v3.1", trust_remote_code=True, device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use tiny-random/deepseek-v3.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tiny-random/deepseek-v3.1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tiny-random/deepseek-v3.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/tiny-random/deepseek-v3.1

SGLang

How to use tiny-random/deepseek-v3.1 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "tiny-random/deepseek-v3.1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tiny-random/deepseek-v3.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "tiny-random/deepseek-v3.1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tiny-random/deepseek-v3.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use tiny-random/deepseek-v3.1 with Docker Model Runner:
```
docker model run hf.co/tiny-random/deepseek-v3.1
```

yujiepan commited on Aug 22, 2025

Commit

0cf9bd4

verified ·

1 Parent(s): 677aeb4

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README.md +3 -3

README.md CHANGED Viewed

@@ -7,10 +7,10 @@ widget:
     example_title: Hello world
     group: Python
 base_model:
-- deepseek-ai/DeepSeek-V3.1-Base
 ---
-This tiny model is for debugging. It is randomly initialized with the config adapted from [deepseek-ai/DeepSeek-V3.1-Base](https://huggingface.co/deepseek-ai/DeepSeek-V3.1-Base).
 ### Example usage:
@@ -62,7 +62,7 @@ from transformers import (
     set_seed,
 )
 from transformers.models.glm4_moe.modeling_glm4_moe import Glm4MoeRMSNorm
-source_model_id = "deepseek-ai/DeepSeek-V3.1-Base"
 save_folder = "/tmp/tiny-random/deepseek-v3.1"
 Path(save_folder).mkdir(parents=True, exist_ok=True)

     example_title: Hello world
     group: Python
 base_model:
+- deepseek-ai/DeepSeek-V3.1
 ---
+This tiny model is for debugging. It is randomly initialized with the config adapted from [deepseek-ai/DeepSeek-V3.1](https://huggingface.co/deepseek-ai/DeepSeek-V3.1).
 ### Example usage:
     set_seed,
 )
 from transformers.models.glm4_moe.modeling_glm4_moe import Glm4MoeRMSNorm
+source_model_id = "deepseek-ai/DeepSeek-V3.1"
 save_folder = "/tmp/tiny-random/deepseek-v3.1"
 Path(save_folder).mkdir(parents=True, exist_ok=True)